Spreadsheet Comprehension: Guesswork, Giving Up and Going Back to the Author
Sruti Srinivasa Ragavan, Advait Sarkar, Andrew D. Gordon
Abstract
Spreadsheet users routinely read, and misread, others' spreadsheets, but literature ofers only a high-level understanding of users' comprehension behaviors. This limits our ability to support millions of users in spreadsheet comprehension activities. Therefore, we conducted a think-aloud study of 15 spreadsheet users who read others' spreadsheets as part of their work. With qualitative coding of participants' comprehension needs, strategies and difculties at 20-second granularity, our study provides the most detailed understanding of spreadsheet comprehension to date.
Participants comprehending spreadsheets spent around 40% of their time seeking additional information needed to understand the spreadsheet. These information seeking episodes were tedious: around 50% of participants reported feeling overwhelmed. Moreover, participants often failed to obtain the necessary information and worked instead with guesses about the spreadsheet. Eventually, 12 out of 15 participants decided to go back to the spreadsheet's author for clarifcations. Our fndings have design implications for reading as well as writing spreadsheets.
• Human-centered computing → Human computer interaction (HCI); Empirical studies in HCI; • Software and its engineering → Software creation and management; Software post-development issues; Maintaining software..
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 8bc35a70-5741-48b9-bfd4-4a32495e3c19Cited by top-tier papers5
- "What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language ModelsMichael Xieyang Liu, Advait Sarkar, Carina Negreanu, Benjamin G. Zorn et al.CHI 2023 · 114 citations
- "It's Freedom to Put Things Where My Mind Wants": Understanding and Improving the User Experience of Structuring Data in SpreadsheetsGeorge Chalhoub, Advait SarkarCHI 2022 · 21 citations
- Table Illustrator: Puzzle-based interactive authoring of plain tablesYanwei Huang, Yurun Yang, Xinhuan Shu, Ran Chen et al.CHI 2024 · 5 citations
- 'How Do You Know That Stuff?': Barriers to Expertise Sharing Among Spreadsheet UsersQing (Nancy) Xia, Advait Sarkar, Duncan P. Brumby, Anna L. CoxCSCW 2025 · 2 citations
- The Invisible Mentor: Inferring User Actions from Screen Recordings to Recommend Better WorkflowsLitao Yan, Andrew Head, Ken Milne, Vu Le et al.CHI 2026
Related papers
- Visual Cues for Data Analysis Features Amplify Challenges for Blind Spreadsheet UsersMinoli Perera, Bongshin Lee, Eun Kyoung Choe, Kim MarriottCHI 2024 · 3 citations
- NOAH: Interactive Spreadsheet Exploration with Dynamic Hierarchical OverviewsSajjadur Rahman, Mangesh Bendre, Yuyang Liu, Shichu Zhu et al.VLDB 2021 · 11 citations
- How To Draw Commands? An Elicitation Study for Sketching on SpreadsheetsMarc Hesenius, Mak Krvavac, Valbjörn Jón Valbjörnsson, Theresia Mita Erika et al.CHI 2025 · 7 citations
- Untidy Data: The Unreasonable Effectiveness of TablesLyn Bartram, Michael Correll, Melanie ToryIEEE VIS 2021 · 56 citations
- Do You See What I See? A Qualitative Study Eliciting High-Level Visualization ComprehensionGhulam Jilani Quadri, Arran Zeyu Wang, Zhehao Wang, Jennifer Adorno Nieves et al.CHI 2024 · 37 citations
